{"id":"https://openalex.org/W4313251329","doi":"https://doi.org/10.1080/0951192x.2022.2163293","title":"A just-in-time learning-based compensation prediction method for hull plate welding","display_name":"A just-in-time learning-based compensation prediction method for hull plate welding","publication_year":2022,"publication_date":"2022-12-27","ids":{"openalex":"https://openalex.org/W4313251329","doi":"https://doi.org/10.1080/0951192x.2022.2163293"},"language":"en","primary_location":{"id":"doi:10.1080/0951192x.2022.2163293","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0951192x.2022.2163293","pdf_url":null,"source":{"id":"https://openalex.org/S57062392","display_name":"International Journal of Computer Integrated Manufacturing","issn_l":"0951-192X","issn":["0951-192X","1362-3052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Integrated Manufacturing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100334633","display_name":"Liang Chen","orcid":"https://orcid.org/0000-0002-8765-4570"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Chen","raw_affiliation_strings":["Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100852789","display_name":"Yu Zheng","orcid":"https://orcid.org/0009-0007-5767-2771"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040123740","display_name":"Kaipeng Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaipeng Lan","raw_affiliation_strings":["Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Intelligent Manufacturing and Information Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100307788","display_name":"Yanjun Ma","orcid":"https://orcid.org/0000-0002-0521-8434"},"institutions":[{"id":"https://openalex.org/I4210091949","display_name":"Shanghai Shipbuilding Technology Research Institute","ror":"https://ror.org/00g2kbc16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210091949"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjun Ma","raw_affiliation_strings":["Institute of Information Technology, Hudong-Zhonghua Shipbuilding (Group) Co., Ltd, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Technology, Hudong-Zhonghua Shipbuilding (Group) Co., Ltd, Shanghai, China","institution_ids":["https://openalex.org/I4210091949"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027776208","display_name":"Huade Su","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091949","display_name":"Shanghai Shipbuilding Technology Research Institute","ror":"https://ror.org/00g2kbc16","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210091949"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huade Su","raw_affiliation_strings":["Institute of Information Technology, Hudong-Zhonghua Shipbuilding (Group) Co., Ltd, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Institute of Information Technology, Hudong-Zhonghua Shipbuilding (Group) Co., Ltd, Shanghai, China","institution_ids":["https://openalex.org/I4210091949"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100852789"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15560486,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":"8","first_page":"1178","last_page":"1190"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10834","display_name":"Welding Techniques and Residual Stresses","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10834","display_name":"Welding Techniques and Residual Stresses","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10705","display_name":"Additive Manufacturing Materials and Processes","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/welding","display_name":"Welding","score":0.692703902721405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4959128797054291},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4535951018333435},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44848334789276123},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.4330846965312958},{"id":"https://openalex.org/keywords/compensation","display_name":"Compensation (psychology)","score":0.4302453100681305},{"id":"https://openalex.org/keywords/hull","display_name":"Hull","score":0.426175594329834},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38638782501220703},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33434998989105225},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2966170907020569},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.18660607933998108},{"id":"https://openalex.org/keywords/marine-engineering","display_name":"Marine engineering","score":0.11186251044273376}],"concepts":[{"id":"https://openalex.org/C19474535","wikidata":"https://www.wikidata.org/wiki/Q131172","display_name":"Welding","level":2,"score":0.692703902721405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4959128797054291},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4535951018333435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44848334789276123},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.4330846965312958},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.4302453100681305},{"id":"https://openalex.org/C37423430","wikidata":"https://www.wikidata.org/wiki/Q6750281","display_name":"Hull","level":2,"score":0.426175594329834},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38638782501220703},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33434998989105225},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2966170907020569},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.18660607933998108},{"id":"https://openalex.org/C199104240","wikidata":"https://www.wikidata.org/wiki/Q118291","display_name":"Marine engineering","level":1,"score":0.11186251044273376},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/0951192x.2022.2163293","is_oa":false,"landing_page_url":"https://doi.org/10.1080/0951192x.2022.2163293","pdf_url":null,"source":{"id":"https://openalex.org/S57062392","display_name":"International Journal of Computer Integrated Manufacturing","issn_l":"0951-192X","issn":["0951-192X","1362-3052"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Integrated Manufacturing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6645873968","display_name":null,"funder_award_id":"No.52075338","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1787066209","https://openalex.org/W1972720327","https://openalex.org/W1996879898","https://openalex.org/W2031162618","https://openalex.org/W2077116923","https://openalex.org/W2085318289","https://openalex.org/W2215543927","https://openalex.org/W2332901007","https://openalex.org/W2473060649","https://openalex.org/W2520634214","https://openalex.org/W2554271521","https://openalex.org/W2742707706","https://openalex.org/W2765135472","https://openalex.org/W2769869717","https://openalex.org/W2783796248","https://openalex.org/W2804079976","https://openalex.org/W2804537987","https://openalex.org/W3000496545","https://openalex.org/W3023056142","https://openalex.org/W3032884617","https://openalex.org/W3088878891","https://openalex.org/W3090028796","https://openalex.org/W3112290742","https://openalex.org/W3133581429"],"related_works":["https://openalex.org/W2467926385","https://openalex.org/W161301265","https://openalex.org/W2483619716","https://openalex.org/W4246461909","https://openalex.org/W2377576908","https://openalex.org/W563487689","https://openalex.org/W2893068807","https://openalex.org/W2971424936","https://openalex.org/W2007256320","https://openalex.org/W2965861863"],"abstract_inverted_index":{"ABSTRACTThe":[0],"accuracy":[1,21,41,78],"of":[2,9,22,33,87,107,149,170,203,210,215,229,236,253,257,262,269,276],"plate":[3,23,34,108,111,191],"welding":[4,35,112,132,192],"substantially":[5],"impacts":[6],"the":[7,10,14,20,31,65,67,72,105,125,131,134,142,147,152,159,167,171,178,198,208,241,248],"quality":[8],"final":[11],"hull":[12,15],"and":[13,56,80,90,212,221,225,259],"construction":[16],"efficiency.":[17],"To":[18,63,129],"control":[19],"welding,":[24],"one":[25],"effective":[26],"method":[27,48],"is":[28],"to":[29,76,96,103,123],"estimate":[30],"extent":[32],"compensation":[36,106,183],"for":[37,60],"planning":[38],"a":[39,47,51],"reasonable":[40],"management":[42],"plan.":[43],"This":[44],"paper":[45],"proposes":[46],"that":[49,99,177],"utilizes":[50],"Gaussian":[52],"mixture":[53,189],"model":[54,156,169,180],"(GMM)":[55],"just-in-time":[57],"learning":[58],"(JITL)":[59],"this":[61],"purpose.":[62],"develop":[64],"method,":[66],"raw":[68],"data":[69,127],"collected":[70],"by":[71,120,158,197,240,247],"shipyard":[73],"were":[74,94],"used":[75,102],"perform":[77],"judgment":[79],"missing":[81],"value":[82],"processing.":[83],"Then,":[84],"correlation":[85],"analysis":[86],"various":[88],"parameters":[89],"feature":[91],"extraction":[92],"methods":[93],"implemented":[95],"extract":[97],"features":[98],"can":[100,114],"be":[101,115,138],"predict":[104],"welding.":[109],"The":[110,174],"process":[113],"divided":[116],"into":[117],"different":[118,126,150],"stages":[119],"using":[121],"GMM":[122],"cluster":[124],"distributions.":[128],"track":[130],"process,":[133],"local":[135,168],"models":[136],"should":[137],"established":[139],"based":[140],"on":[141,266],"JITL":[143,172],"principle.":[144],"By":[145],"comparing":[146],"performance":[148],"models,":[151],"support":[153],"vector":[154],"regression":[155],"optimized":[157],"particle":[160],"swarm":[161],"optimization":[162],"algorithm":[163],"was":[164,195,238,245],"applied":[165],"as":[166],"model.":[173],"results":[175],"demonstrated":[176],"proposed":[179],"yields":[181],"excellent":[182],"prediction":[184],"performance.KEYWORDS:":[185],"Compensation":[186],"predictionjust-in-time":[187],"learningGaussian":[188],"modelhull":[190],"AcknowledgementsThis":[193],"research":[194],"supported":[196,246],"National":[199,249],"Natural":[200,250],"Science":[201,251],"Foundation":[202,252],"China":[204,216,254,263],"under":[205,217],"Grant":[206,218,222],"No.52075338,":[207],"Ministry":[209,256],"Industry":[211,258],"Information":[213,260],"Technology":[214,261],"No.":[219,223,279],"MC-201720-Z02":[220],"CJ04N20,":[224],"Shanghai":[226],"Key":[227,267],"lab":[228],"Advanced":[230],"Manufacturing":[231],"Environment.Disclosure":[232],"statementNo":[233],"potential":[234],"conflict":[235],"interest":[237],"reported":[239],"author(s).Additional":[242],"informationFundingThe":[243],"work":[244],"[No.52075338];":[255],"[MC-201720-Z02];":[264],"Research":[265],"Technologies":[268],"5G":[270],"Application":[271],"in":[272],"Block":[273],"Assembly":[274],"Workshop":[275],"Shipbuilding":[277],"[Grant":[278],"CJ04N20].":[280]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}